30 min
RT3. AI Hardware Introduction Paul, Deon & Tong
-
- Tech News
This is another sort of nerdy side note. If anyone is still watching, this section is just to give intuition on the basics of the hardware. There are lots of assumptions about GPUs and CPUs that I wanted to make sure people understood.But the basics are that CPUs are tuned for lots of branches and different workflows, while GPUs are tuned for lots of the same things like matric math. And because they are so fast, most of the job of the computer folks is "feeding the beast". That is caching the most frequently used information so they don't have to wait.
There are some errors I think in the levels of the CPU and GPU performance particularly in the cache performance as it is not very clear how this works and the results of course vary depending on the models of processors, so these are all approximations. Put in comments better sources. I have all the sources listed in a spreadsheet that is part of this. We are happy to send this to anyone who wants the source data. I'll fix these errors in later editions (as I'm obsessive that way)
.Also, I'm quite proud of the HDR mix, using the latest OBS settings, producing in HDR in Final Cut Pro, and adjusting the video scope levels helps. The audio is a little hot and I'm sorry about that, I'll turn it down next time, I stoo much time in the red. My Scarlett needs to about 1 O'clock and it works.
See https://youtu.be/FupclouzYTI for a video version. And more details at https://tongfamily.com/2024/03/08/pod-rt3-ai-hardware-introduction/
Chapters:
00:00 AI Hardware Introduction
00:42 Computer Engineering in Two Slides
05:40 It's 165 Years to a Single Disk Access?!!
14:12 Intel Architecture CPU
17:03 What's all this about NVidia
25:24 And now for something completely different, Apple
29:45 Introduction Summary
2024-03 -08 Shot as UHD HEVC HDR PQ 10 bit using OBS Studio and Final Cut Pro© 2024. Iron Snow Technologies, LLC. All Rights Reserved.
---
Send in a voice message: https://podcasters.spotify.com/pod/show/richt/message
This is another sort of nerdy side note. If anyone is still watching, this section is just to give intuition on the basics of the hardware. There are lots of assumptions about GPUs and CPUs that I wanted to make sure people understood.But the basics are that CPUs are tuned for lots of branches and different workflows, while GPUs are tuned for lots of the same things like matric math. And because they are so fast, most of the job of the computer folks is "feeding the beast". That is caching the most frequently used information so they don't have to wait.
There are some errors I think in the levels of the CPU and GPU performance particularly in the cache performance as it is not very clear how this works and the results of course vary depending on the models of processors, so these are all approximations. Put in comments better sources. I have all the sources listed in a spreadsheet that is part of this. We are happy to send this to anyone who wants the source data. I'll fix these errors in later editions (as I'm obsessive that way)
.Also, I'm quite proud of the HDR mix, using the latest OBS settings, producing in HDR in Final Cut Pro, and adjusting the video scope levels helps. The audio is a little hot and I'm sorry about that, I'll turn it down next time, I stoo much time in the red. My Scarlett needs to about 1 O'clock and it works.
See https://youtu.be/FupclouzYTI for a video version. And more details at https://tongfamily.com/2024/03/08/pod-rt3-ai-hardware-introduction/
Chapters:
00:00 AI Hardware Introduction
00:42 Computer Engineering in Two Slides
05:40 It's 165 Years to a Single Disk Access?!!
14:12 Intel Architecture CPU
17:03 What's all this about NVidia
25:24 And now for something completely different, Apple
29:45 Introduction Summary
2024-03 -08 Shot as UHD HEVC HDR PQ 10 bit using OBS Studio and Final Cut Pro© 2024. Iron Snow Technologies, LLC. All Rights Reserved.
---
Send in a voice message: https://podcasters.spotify.com/pod/show/richt/message
30 min